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--- |
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language: id |
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tags: |
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- gpt2-indo-small-kids-stories |
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license: mit |
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widget: |
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- text: "Archie sedang mengendarai roket ke planet Mars." |
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--- |
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## GPT-2 Indonesian Small Kids Stories |
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GPT-2 Indonesian Small Kids Stories is a causal language model based on the [OpenAI GPT-2](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) model. The model was originally the pre-trained [GPT2 Small Indonesian](https://huggingface.co/flax-community/gpt2-small-indonesian) model, which was then fine-tuned on Indonesian kids' stories from [Room To Read](https://literacycloud.org/) and [Let's Read](https://reader.letsreadasia.org/). |
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10% of the dataset was kept for evaluation purposes. The pre-trained model was fine-tuned and achieved an evaluation loss of 3.777 and an evaluation perplexity of 43.68. |
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Hugging Face's `Trainer` class from the [Transformers](https://huggingface.co/transformers) library was used to train the model. PyTorch was used as the backend framework during training, but the model remains compatible with other frameworks nonetheless. |
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## Model |
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| Model | #params | Arch. | Training/Validation data (text) | |
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| ------------------------------ | ------- | ---------- | --------------------------------- | |
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| `gpt2-indo-small-kids-stories` | 124M | GPT2 Small | Indonesian Kids' Stories (860 KB) | |
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## Evaluation Results |
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The model was fine-tuned for 10 epochs. |
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| Epoch | Training Loss | Validation Loss | |
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| ----- | ------------- | --------------- | |
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| 1 | 4.259600 | 4.020201 | |
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| 2 | 3.979100 | 3.911295 | |
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| 3 | 3.818300 | 3.849313 | |
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| 4 | 3.691600 | 3.809931 | |
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| 5 | 3.589300 | 3.789201 | |
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| 6 | 3.506200 | 3.778665 | |
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| 7 | 3.439200 | 3.774871 | |
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| 8 | 3.387600 | 3.774859 | |
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| 9 | 3.351300 | 3.776672 | |
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| 10 | 3.330100 | 3.776935 | |
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## How to Use (PyTorch) |
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### As Causal Language Model |
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```python |
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from transformers import pipeline |
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pretrained_name = "bookbot/gpt2-indo-small-kids-stories" |
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nlp = pipeline( |
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"text-generation", |
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model=pretrained_name, |
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tokenizer=pretrained_name |
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) |
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nlp("Archie sedang mengendarai roket ke planet Mars.") |
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``` |
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### Feature Extraction in PyTorch |
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```python |
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from transformers import GPT2LMHeadModel, GPT2TokenizerFast |
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pretrained_name = "bookbot/gpt2-indo-small-kids-stories" |
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model = GPT2LMHeadModel.from_pretrained(pretrained_name) |
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tokenizer = GPT2TokenizerFast.from_pretrained(pretrained_name) |
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prompt = "Archie sedang mengendarai roket ke planet Mars." |
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encoded_input = tokenizer(prompt, return_tensors='pt') |
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output = model(**encoded_input) |
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``` |
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## Disclaimer |
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Do consider the biases which come from both the pre-trained GPT-2 model and the Indonesian Kids' Stories dataset that may be carried over into the results of this model. |
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## Author |
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GPT-2 Indonesian Small Kids Stories was trained and evaluated by [Wilson Wongso](https://w11wo.github.io/). All computation and development are done on Google Colaboratory using their free GPU access. |
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